Genomic and transcriptomic analyses support a silk gland origin of spider venom glands
Bibliographic record
Abstract
BACKGROUND: Spiders comprise a hyperdiverse lineage of predators with venom systems, yet the origin of functionally novel spider venom glands remains unclear. Previous studies have hypothesized that spider venom glands originated from salivary glands or evolved from silk-producing glands present in early chelicerates. However, there is insufficient molecular evidence to indicate similarity among them. Here, we provide comparative analyses of genome and transcriptome data from various lineages of spiders and other arthropods to advance our understanding of spider venom gland evolution. RESULTS: We generated a chromosome-level genome assembly of a model spider species, the common house spider (Parasteatoda tepidariorum). Module preservation, GO semantic similarity, and differentially upregulated gene similarity analyses demonstrated a lower similarity in gene expressions between the venom glands and salivary glands compared to the silk glands, which questions the validity of the salivary gland origin hypothesis but unexpectedly prefers to support the ancestral silk gland origin hypothesis. The conserved core network in the venom and silk glands was mainly correlated with transcription regulation, protein modification, transport, and signal transduction pathways. At the genetic level, we found that many genes in the venom gland-specific transcription modules show positive selection and upregulated expressions, suggesting that genetic variation plays an important role in the evolution of venom glands. CONCLUSIONS: This research implies the unique origin and evolutionary path of spider venom glands and provides a basis for understanding the diverse molecular characteristics of venom systems.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".